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Mathematical Problems in Engineering
Volume 2014, Article ID 417129, 11 pages
http://dx.doi.org/10.1155/2014/417129
Research Article

How to Choose “Last Mile” Delivery Modes for E-Fulfillment

1Institute of Systems Engineering, Dalian University of Technology, Dalian 116024, China
2School of Business, Dalian University of Technology, Panjin 124221, China
3School of Electrical and Electronic Engineering, Faculty of Engineering, Computer and Mathematical Sciences, University of Adelaide, Adelaide, SA 5005, Australia

Received 11 February 2014; Revised 1 May 2014; Accepted 15 May 2014; Published 11 June 2014

Academic Editor: Kwok-Wo Wong

Copyright © 2014 Xuping Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Linked References

  1. J.-C. Pai and C.-H. Yeh, “Factors affecting the implementation of e-business strategies: an empirical study in Taiwan,” Management Decision, vol. 46, no. 5, pp. 681–690, 2008. View at Publisher · View at Google Scholar · View at Scopus
  2. China Internet Network Information Center, “China’s online shopping market research report in 2012,” April 2007 (Chinese), http://www.cnnic.cn/hlwfzyj/hlwxzbg/dzswbg/201304/t20130417_39290.htm.
  3. China Enterprise News, “Optimization of logistics distribution chain, solve last mile delivery problem,” September 2013 (Chinese), http://info.jctrans.com/news/synthetic_trans/20139121967744.shtml.
  4. V. Kupke, P. Rossini, and S. McGreal, “Measuring the impact of higher density housing development,” Property Management, vol. 30, no. 3, pp. 274–291, 2012. View at Publisher · View at Google Scholar · View at Scopus
  5. P. J. Smailes, N. Argent, and T. L. C. Griffin, “Rural population density: its impact on social and demographic aspects of rural communities,” Journal of Rural Studies, vol. 18, no. 4, pp. 385–404, 2002. View at Publisher · View at Google Scholar · View at Scopus
  6. K. K. Boyer, A. M. Prud'homme, and W. Chung, “The last mile challenge: evaluating the effects of customer density and delivery window patterns,” Journal of Business Logistics, vol. 30, no. 1, pp. 185–201, 2009. View at Google Scholar
  7. N. Agatz, A. Campbell, M. Fleischmann, and M. Savelsbergh, “Time slot management in attended home delivery,” Transportation Science, vol. 45, no. 3, pp. 435–449, 2011. View at Publisher · View at Google Scholar · View at Scopus
  8. A. V. Hill, J. M. Hays, and E. Naveh, “A model for optimal delivery time guarantees,” Journal of Service Research, vol. 2, no. 3, pp. 254–264, 2000. View at Publisher · View at Google Scholar
  9. M. A. Bushuev and A. L. Guiffrida, “Optimal position of supply chain delivery window: concepts and general conditions,” International Journal of Production Economics, vol. 137, no. 2, pp. 226–234, 2012. View at Publisher · View at Google Scholar · View at Scopus
  10. A. M. Campbell and M. Savelsbergh, “Incentive schemes for attended home delivery services,” Transportation Science, vol. 40, no. 3, pp. 327–341, 2006. View at Publisher · View at Google Scholar · View at Scopus
  11. M. Punakivi, H. Yrjölä, and J. Holmström, “Solving the last mile issue: reception box or delivery box,” International Journal of Physical Distribution & Logistics Management, vol. 31, no. 6, pp. 427–439, 2001. View at Publisher · View at Google Scholar
  12. M. Punakivi and K. Tanskanen, “Increasing the cost efficiency of e-fulfilment using shared reception boxes,” International Journal of Retail & Distribution Management, vol. 30, no. 10, pp. 498–507, 2002. View at Publisher · View at Google Scholar
  13. J. W. J. Weltevreden, “B2c e-commerce logistics: the rise of collection-and-delivery points in The Netherlands,” International Journal of Retail & Distribution Management, vol. 36, no. 8, pp. 638–660, 2008. View at Publisher · View at Google Scholar · View at Scopus
  14. H. L. Lee and S. Whang, “Winning the last mile of e-commerce,” MIT Sloan Management Review, vol. 42, no. 4, pp. 54–62, 2001. View at Google Scholar · View at Scopus
  15. L. Song, T. Cherrett, F. McLeod, and W. Guan, “Addressing the last mile problem-the transport impacts of collection/delivery points,” in Proceedings of the 88th Annual Meeting of the Transportation Research Board, 2009.
  16. F. McLeod, T. Cherrett, and L. Song, “Transport impacts of local collection/delivery points,” International Journal of Logistics, vol. 9, no. 3, pp. 307–317, 2006. View at Google Scholar
  17. Y. Yi and T. Gong, “The effects of customer justice perception and affect on customer citizenship behavior and customer dysfunctional behavior,” Industrial Marketing Management, vol. 37, no. 7, pp. 767–783, 2008. View at Publisher · View at Google Scholar · View at Scopus
  18. Z. Ursani, D. Essam, D. Cornforth, and R. Stocker, “Localized genetic algorithm for vehicle routing problem with time windows,” Applied Soft Computing, vol. 11, no. 8, pp. 5375–5390, 2011. View at Publisher · View at Google Scholar · View at Scopus
  19. R. Liu, X. Xie, V. Augusto, and C. Rodriguez, “Heuristic algorithms for a vehicle routing problem with simultaneous delivery and pickup and time windows in home health care,” European Journal of Operational Research, vol. 230, no. 3, pp. 475–486, 2013. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  20. V. Pureza, R. Morabito, and M. Reimann, “Vehicle routing with multiple deliverymen: modeling and heuristic approaches for the VRPTW,” European Journal of Operational Research, vol. 218, no. 3, pp. 636–647, 2012. View at Publisher · View at Google Scholar · View at MathSciNet · View at Scopus
  21. J. Ruan, X. Wang, Y. Shi, and Z. Sun, “Scenario-based path selection in uncertain emergency transportation networks,” International Journal of Innovative Computing, Information & Control, vol. 9, no. 8, pp. 3293–3305, 2013. View at Google Scholar · View at Scopus
  22. X. Wang, J. Ruan, and Y. Shi, “A recovery model for combinational disruptions in logistics delivery: considering the real-world participators,” International Journal of Production Economics, vol. 140, no. 1, pp. 508–520, 2012. View at Publisher · View at Google Scholar · View at Scopus
  23. F. P. Goksal, I. Karaoglan, and F. Altiparmak, “A hybrid discrete particle swarm optimization for vehicle routing problem with simultaneous pickup and delivery,” Computers & Industrial Engineering, vol. 65, no. 1, pp. 39–53, 2013. View at Publisher · View at Google Scholar · View at Scopus
  24. J. Ruan, X. Wang, and Y. Shi, “Developing fast predictors for large-scale time series using fuzzy granular support vector machines,” Applied Soft Computing, vol. 13, no. 9, pp. 3981–4000, 2012. View at Publisher · View at Google Scholar · View at Scopus
  25. R. Dondo and J. Cerdá, “A cluster-based optimization approach for the multi-depot heterogeneous fleet vehicle routing problem with time windows,” European Journal of Operational Research, vol. 176, no. 3, pp. 1478–1507, 2007. View at Publisher · View at Google Scholar · View at Scopus
  26. G. di Fatta, F. Blasa, S. Cafiero, and G. Fortino, “Fault tolerant decentralised K-means clustering for asynchronous large-scale networks,” Journal of Parallel and Distributed Computing, vol. 73, no. 3, pp. 317–329, 2013. View at Publisher · View at Google Scholar · View at Scopus
  27. F. An and H. J. Mattausch, “K-means clustering algorithm for multimedia applications with flexible HW/SW co-design,” Journal of Systems Architecture, vol. 59, no. 3, pp. 155–164, 2012. View at Publisher · View at Google Scholar · View at Scopus
  28. J. Ruan, X. Wang, and Y. Shi, “A clustering-based approach for emergency medical supplies transportation in large-scale disasters,” ICIC Express Letters, vol. 8, no. 1, pp. 187–193, 2014. View at Google Scholar
  29. M. Punakivi and J. Saranen, “Identifying the success factors in e-grocery home delivery,” International Journal of Retail & Distribution Management, vol. 29, no. 4, pp. 156–163, 2001. View at Google Scholar